辽东湾海水透明度的遥感估算模型

doi:10.11867/j.issn.1001-8166.2011.03.0295

地球科学进展 ›› 2011, Vol. 26 ›› Issue (3): 295 -299. doi: 10.11867/j.issn.1001-8166.2011.03.0295

辽东湾海水透明度的遥感估算模型

丛丕福 ¹，曲丽梅 ¹，韩庚辰 ¹，杨新梅 ¹，王臣立 ²

1.国家海洋环境监测中心，辽宁大连116023；
2. 中国文化遗产研究院，北京100029

收稿日期:2010-03-17 修回日期:2010-12-01 出版日期:2011-03-10
通讯作者: 丛丕福 E-mail:transco@sohu.com
基金资助:
海洋公益性行业科研专项“海洋特别保护区保护利用调控技术及应用示范”（编号：200905011）；国家海洋局近岸海域生态环境重点实验室资助项目(编号：200806)；海洋公益性行业科研专项“海岸带主体功能区的划分方法研究与示范”（编号：200905005）资助.

Remotely Sensed Estimation Model of Ocean Water Transparency in Liaodong Gulf

Cong Pifu ¹, Qu Limei ¹, Han Gengchen ¹，Yang Xinmei ¹, Wang Chenli ²

1.National Marine Environmental Monitoring Center, Dalian116023,China;
2. Chinese Academy of Cultural Heritage, Beijing100029,China

Received:2010-03-17 Revised:2010-12-01 Online:2011-03-10 Published:2011-03-10

下载PDF ( 1496 )

海水透明度和水质存在很好的相关性，是水质的重要量度之一。利用卫星遥感估算获取透明度可弥补常规采样方法的数据离散化、耗时长且费用高的缺陷，可得到大尺度海洋透明度分布。以辽东湾为研究区，利用现场实测光谱模拟了MODIS波段从而削除大气干扰，在分析MODIS特征波段基础上，通过比较单波段算法和波段比值法等算法，建立了透明度遥感估算模型，并进行了模型验证。结果表明：在辽东湾海域，MODIS 667 nm波段和透明度的相关性最好，而且单波段建立的估算模型要优于其他特征波段的组合。未考虑传统的蓝绿波段的667 nm单波段二次多项式估算模型相关系数r为0.973(p<0.01),检验平均相对误差13％，表明了模型稳定而有良好的预测能力。模型具有明显的区域特色，结果是否具有普适性，还需进一步验证。

关键词: 辽东湾, 透明度, MODIS, 遥感

As one of the important indicators which describe water visibility and optical property,ocean water transparency has good relationship with water quality. Measurement of ocean water transparency from satellite remotely sensed image can compensate for the deficiencies of discrete data, long time and expensive cost of field measurement.Moreover, it can obtain the large-scale distribution of ocean water transparency. So it can be applied to long term observation of ocean water transparency at large scale. Liaodong Gulf was selected as the study area. Ocean water reflectance of MODIS bands were simulated to reduce the disturbance of atmosphere based on in situ filed measurement spectrum. According to the spectral simulation, characteristic bands of MODIS were indentified for water transparency estimation model. The correlationship was respectively ananlyzed in Liaodong Gulf. Then the estimation model of water transparency using MODIS of the area was developed and the model test was also performed. The result shows that in Liaodong Gulf, the band of 667 nm of MODIS has the best correlation with ocean water transparency.Moreover, the estimation model based on single band performs better than band combine approach such as band ratio. Without the incorporation of the classical bands of blue and green bands for oceancolor remote sensing, the estimation model of two-order polynomial of single band 667 nm has the correlation coefficient r of 0.973(p<0.01) and the relative mean error of model test is 13％. It shows the stability and good forecast performance of the model. As the model was developed based on the dataset of area of the experiment, it has distinct local character. It needs further study to test whether it can be applied to other areas.

Key words: Liaodong Gulf, Water transparency, MODIS, Remote sensing

中图分类号:

P731.14
X55

[1] Xia Guanghui,Yu Yide,Xiong Ying. Study on a new method of measurement of seawater transparency[J].Marine Environmental Science, 2009,28(3):316-328.[夏光辉,余义德,熊英.一种海水透明度测量新方法的研究与实现[J].海洋环境科学,2009,28(3):316-328.]
[2] Li Yinghong,Wang Fan,Ren Xiaobo. Developmeng trend and strategy of ocean observing capability[J]. Advances in Earth Science, 2010, 25(7):715-722.[李颖虹,王凡,任小波. 海洋观测能力建设的现状、趋势与对策思考[J].地球科学进展, 2010, 25(7):715-722.]
[3] Tang Shilin,Chen Chuqun,Zhan Haigang,et al.Retrieval of euphotic layer depth of South China Sea by remote sensing[J]. Journal of Tropical Oceanography, 2007,26(1):9-15.[唐世林,陈楚群,詹海刚,等.南海真光层深度的遥感反演[J].热带海洋学报,2007,26(1):9-15.]
[4] Koponen S, Pulliainen J, Kallio K, et al. Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data[J].Remote Sensing of Environment, 2002,79: 51-59.
[5] Wang Xiaomei,Tang Junwu,Ding Jing,et al. The retrieval algorithms of diffuse attenuation and transparency for the CaseⅡwaters of the Huanghai Sea and the East China Sea[J].Acta Oceanologica Sinica, 2005,27(5): 38-45.[王晓梅,唐军武,丁静,等.黄海、东海二类水体漫衰减系数与透明度反演模式研究[J]. 海洋学报,2005,27(5): 38-45.]
[6] Wang Deyu,Feng Xuezhi. Analysis of temporal and spatial changes of water clority based in TM image in the estuany of Qiantang river[J].Journal of Jiangxi Normal University(Natural Sciences Edition),2005,29(2):185-189.[王得玉,冯学智．基于TM影像的钱塘江人海口水体透明度的时空变化分析[J]．江西师范大学学报:自然科学版,2005,29(2)：185-189.]
[7] Hellweger F L, Schlosser P, Lall U, et al. Use of satellite imagery for water quality studies in New York Harbor[J]. Estuarine, Coastal and Shelf Science,2004,61:437-448.
[8]He Xiande,Pan Delu, Mao Zhihua,et al. The study on the inversing model of water transparencyusing the SeaWiFS data[J].Acta Oceanologica Sinica,2004,26(5):55-62.[何贤德，潘德炉，毛志华, 等.利用SeaWiFS反演海水透明度的模式研究[J].海洋学报,2004,26(5):55-62.]
[9]Moore T S, Campbell J W, Dowell M D.A classbased approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product[J]. Remote Sensing of Environment,2009, 113(11):2 424-2 430.
[10] Xing Qianguo.Retrieval of Water Quality in the Pearl River Estuary Using Hyperspetral Technique[D]. Guangzhuo:South China Sea Institute of Oceanology, Chinese Academy of Sciences,2007.[邢前国.珠江口水质高光谱反演[D].广州：中国科学院南海海洋研究所,2007.]
[11] Ma Yi.Red Tide Airborne Hyperspectral Remote Sensing Detecting Technology[D]. Qingdao:Institute of Oceanology, Chinese Academy of Sciences,2003.[马毅.赤潮航空高光谱遥感探测技术研究[D].青岛：中国科学院海洋研究所,2003.]
[12] Cong Pifu, Niu Zhen, Qu Limei, et al. Retrieval of chlorophyll a concentration from ocean satellite HY-1[J]. High Technology Letters, 2005,15(11):106-110.[丛丕福,牛铮,曲丽梅,等. 利用海洋卫星HY-1数据反演叶绿素a的浓度[J].高技术通讯，2005,15(11):106-110].
[13] Li Sihai translated. The Mechanism and Application of Ocean Color Remote Sensing: Report of International Ocean Colour Coordinating Group（IOCCG）[M]. Beijing: Ocean Press,2002.[李四海,译.海洋水色遥感原理与应用:国际海洋水色协调工作组（IOCCG）报告[M].北京: 海洋出版社,2002].

[1]	方迎波, 占文凤, 黄帆, 高伦, 全金玲, 邹照旭. 长三角城市群表面城市热岛日内逐时变化规律[J]. 地球科学进展, 2017, 32(2): 187-198.
[2]	李大治, 晋锐, 车涛, 高莹, 耶楠, 王树果. 联合机载PLMR微波辐射计和MODIS产品反演黑河中游张掖绿洲土壤水分研究 ^*[J]. 地球科学进展, 2014, 29(2): 295-305.
[3]	崔月菊，杜建国，陈志，李静，谢超，周晓成，刘雷. 2010年玉树Ms 7.1地震前后大气物理化学遥感信息[J]. 地球科学进展, 2011, 26(7): 787-794.
[4]	宋平, 刘元波, 刘燕春. 陆地水体参数的卫星遥感反演研究进展[J]. 地球科学进展, 2011, 26(7): 731-740.
[5]	文军，蓝永超，苏中波，田辉，史小康，张宇，王欣，刘蓉，张堂堂，康悦，吕少宁，张静辉. 黄河源区陆面过程观测和模拟研究进展[J]. 地球科学进展, 2011, 26(6): 575-586.
[6]	郑有飞，董自鹏，吴荣军，李占清，江洪. MODIS气溶胶光学厚度在长江三角洲地区适用性分析[J]. 地球科学进展, 2011, 26(2): 224-234.
[7]	卢善龙，吴炳方，闫娜娜，李发鹏，文美平，王京. 河川径流遥感监测研究进展[J]. 地球科学进展, 2010, 25(8): 820-826.
[8]	顾娟,李新,黄春林. 基于时序MODIS NDVI的黑河流域土地覆盖分类研究[J]. 地球科学进展, 2010, 25(3): 317-326.
[9]	张廷军,晋锐,高峰. 冻土遥感研究进展——可见光、红外及主动微波卫星遥感方法[J]. 地球科学进展, 2009, 24(9): 963-972.
[10]	柴琳娜,屈永华,张立新,梁顺林,王锦地. 基于自回归神经网络的时间序列叶面积指数估算[J]. 地球科学进展, 2009, 24(7): 756-768.
[11]	徐春亮,陈彦,贾明权,刘增灿,卢海平,童玲. 典型地物后向散射特性的测量与分析[J]. 地球科学进展, 2009, 24(7): 810-816.
[12]	冉有华,李新,王维真,晋锐. 黑河流域临泽盐碱化草地网格尺度多层土壤水分时空稳定性分析[J]. 地球科学进展, 2009, 24(7): 817-824.
[13]	张廷军,晋锐,高峰. 冻土遥感研究进展：被动微波遥感[J]. 地球科学进展, 2009, 24(10): 1073-1083.
[14]	严燕儿，赵斌，郭海强，吴千红. 生态系统碳通量估算中耦合涡度协方差与遥感技术研究进展[J]. 地球科学进展, 2008, 23(8): 884-894.
[15]	申彦波，王标，石广玉. 2006年春季我国东部海域气溶胶光学厚度与沙尘天气[J]. 地球科学进展, 2008, 23(3): 290-298.

阅读次数

全文

摘要